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Tutorial

What is OBOE?

OBOE stands for the Extensible Observation Ontology. OBOE was designed specificallyto accurately describe observational data in sufficient detail, and using technology, thatfacilitates logic-based machine reasoning to help scientists with common research taskssuch as finding and merging data sets.

What is an ontology?

Ontologies are formal models that define concepts and their relationships within ascientific domain like ecology. Analogous to mathematical set theory, an ontological“concept” (i.e., set) denotes a collection of “instances” that share common characteristics.The backbone of ontologies is the ‘is-a’ relationship, which states that all instances of asub-concept (i.e., subset) are also members of a super-concept and therefore inherit allcharacteristics of the super-concept (Figure 1). For example, Tree would generally bedefined as a sub-concept of Plant. There are other commonly used relationships thatdescribe how concepts interact, including ‘part-of’ (or, conversely, ‘has-part’),‘equivalence’, and ‘disjoint’ relations. In a part-whole (i.e., ‘part-of’ or ‘has-part’)relationship, the instances of one concept (e.g., Tree Branch) are components of instancesof another concept (e.g., Tree). These relationships are constrained by the number ofinstances permitted in the relationship using cardinality restrictions (e.g., a Tree Branchcan only be ‘part-of’ one Tree). In an ‘equivalence’ relationship, two concepts denote thesame set of instances (e.g., Animals andMetazoans), whereas in a ‘disjoint’ relationship,the instances of the two concepts are mutually exclusive (e.g., Plants and Animals).Relationships and cardinality restrictions are inherited through ‘is-a’ relationships; e.g.,instances of the Deme concept have two or more Organism instances as parts, becauseDeme is a sub-concept of Population.

Figure 1.

An ontology fragment representing some Biological-Entity concepts and theirrelationships. In this graphical notation, ellipses denote concepts, arrows denoterelationships, and cardinality restrictions are given in parentheses. For example, anyinstance of Tree Branch is a part of one and only one (i.e., 1:1) instance of a Tree; but,conversely, an instance of Tree has at least two or more (i.e., 2:n) parts that are instancesof Biological Part, because ‘has-part’ relationships and cardinality are inherited fromsuper-concepts. This ontology represents only one interpretation of the domainBiological Entity, where other interpretations can similarlybe described and possiblyinterrelated using different ontologies.

Ontology modeling languages such as the Web Ontology Language (OWL) [30] for theSemantic Web [31] are based on a sub-family of mathematical logic called ‘descriptionlogic’ [22]. The formal underpinnings of these languages offer advantages over lessformal approaches such as controlled vocabularies, thesauri, and concept maps. Forexample, ontology languages allow precise expressions of the meaning of a scientificassertion that can be checked for consistency and compared with other formal assertions.Through automated reasoning techniques, it is possible to automate the process ofdetermining whether an ontology is internally consistent and to infer new relationshipsbetween concepts (beyond those explicitly given in the ontology). For example, inFigure I although Barnacles have Biological Parts (i.e., Barnacle ‘is-a’ Animal, Animal‘is-a’ Organism, and Organism ‘has-part’ Biological Part), and Tree Branches areBiological Parts (i.e.,Tree Branch ‘is-a’ Biological Part), Barnacles cannot have TreeBranches because Animals are ‘disjoint’ from Plants. Although these relationshipimplications may be obvious to scientists, ontologies enable computers to deduce theimplications of long chains of these formal assertions.